Use of focused light scattering techniques in biological applications

ABSTRACT

Methods for using focused light scattering techniques for the optical sensing of biological particles suspended in a liquid medium are disclosed. The optical sensing enables one to characterize particles size and/or distribution in a given sample. This, in turn, allows one to identify the biological particles, determine their relative particle density, detect particle shedding, and identify particle aggregation. The methods are also useful in screening and optimizing drug candidates, evaluating the efficacy and dosage levels of such drugs, and in personalized medicine applications.

CROSS REFERENCE TO RELATED APPLICATIONS

This application claims the priority of U.S. Provisional PatentApplication No. 61/086,675 filed Aug. 6, 2008 in the U.S. Patent andTrademark Office. The disclosure of the foregoing application is herebyincorporated herein by reference in its respective entirety, for allpurposes, and the priority of such provisional application is herebyclaimed under the provisions of 35 USC §119(e).

FIELD OF THE INVENTION

The invention relates generally to methods of using optical sensing ofbiological particles suspended in a liquid medium, and, moreparticularly to optical sensing of particles to determine size and/ornumber of particles. The methods are useful in screening and optimizingdrug candidates, evaluating the efficacy and dosage levels of suchdrugs, and in developing approaches for personalized medicine.

BACKGROUND OF THE INVENTION

It is often essential to characterize biological particles by theirsize, surface condition, states of activation of any surface receptors,distribution, and the like. This information is useful in cell-basedassays and other processes that rely upon those characteristics.Additionally, it is useful in certain diagnostic applications to detectknown changes of the surface of a biological particle. Accordingly, itcan be desirable to detect the surface and monitor changes to thesurface in an efficient and accurate manner.

“Electrophoretic Quasi-Elastic Light Scattering” (EQELS) is one methodfor characterizing biological particles. This method useselectrophoresis that is dependent on the particle's surface chargedensity to identify and characterize suspended biological particles.EQELS uses cells placed in an electric field, where the surface chargeof the particle will determine how that particle moves in the electricfield. Monitoring the electrophoretic mobility of the cells providesinformation useful in distinguishing among different particles in thefield. One can screen and optimize drug candidates which interact withthe biological particles by comparing the spectra of the particlesalone, or bound to the drug candidates.

Coulter counters can also be used to characterize biological particles.These devices are primarily used to count and size cells and otherbiological particles. The Coulter Counter works by drawing fluidcontaining the biological particle through a small opening locatedwithin a current between two electrodes. As the fluid is drawn throughthe opening, the biological particles flow through the current andmeasurably displace a portion of the current. The measurabledisplacement is translated to a pulse that is digitally processed by theCoulter Counter and translated to allow one to characterize the size andnumber of biological particles in the fluid.

Flow cytometry can also be used to characterize biological particles.Flow cytometry uses a beam of light, such as a laser, trained on a fluidto characterize, count and optionally sort particles in the fluid. Thefluid is focused into a stream, and detectors at the intersection of thelight and the fluid stream determine scatter—both forward and side.Additionally, a fluorescent detector may be present to detectfluorescent or fluorescently-tagged particles. One can determine variousphysical and chemical characteristics of each individual particle byanalyzing the detected pattern.

These methods are useful in detecting and characterizing microparticles,including determinating the number of particles, density within a fluidmedium, size, and surface characteristics of the particle, confirmingbinding, or lack thereof, and the like. The microparticles are generallyin the size of between 0.1 μm and 100 μm. However, developments intechnology demand the characterization of smaller biological particles,including, but not limited to, nanoparticles.

The size of biological particles that can be analyzed using currentlyavailable technology is limited. Accordingly, there is a need forprocesses for characterizing biological particles that can detectbiological particles of varying sizes, including particles smaller thanmicroparticles, and which can characterize the detected particles withaccuracy, quantify the particles and/or monitor the particles. Thepresent invention provides such processes.

SUMMARY OF THE INVENTION

The present invention relates to methods of detecting sizes anddistributions of biological particles using focused light scatteringtechniques, and using this information to diagnose disease, identifytherapeutic agents, and obtain other useful information about biologicalparticles and/or therapeutic agents in a sample medium. Representativeparticle sizes that can be measured range from between about 0.1 μm toabout 100 μm, more typically in the range of between about 0.1 and about20 μm.

Using focused light scattering techniques, significantly smallerparticles can be detected than if techniques such as EQELS, flowcytometry, and other conventional methods of measuring biologicalparticles are used. Mathematical algorithms described herein can enableone to not only detect small particles, but also to determine a range ofparticle sizes, relative quantities of such particles, and shapes of theparticles.

Briefly, focused light scattering techniques involve passing a samplemedia through a particular path, where a focused beam of light passesthrough the sample media. The focused beam is of a size such that aparticle in the size range of 0.1 to 10 μm is sufficient to block all ofthe beam, or a significant enough part of the beam, so that the particlesize can be measured.

When there are no particles passing through the pathway of the beam, thebeam passes through the media and onto a detector. When a particle, orpart of a particle, passes through the beam, the beam is deflected. Adiminished amount of light, or no light at all, then reaches thedetector, thus indicating that a particle (or part of a particle) hasinteracted with the beam. The amount of diminished light reaching thedetector provides information about the size of the particle. This isrepeated as particles in the sample medium pass through the beam, forexample, until the sample medium has entirely passed through the beam.Appropriate algorithms then take the information, and the output is aspectrum showing the particle size and particle distribution.

Cells are one type of biological particle that can be detected. Themethod can be used to determine the presence or absence of a specifictype of cell in a given solution. For example, a sample of blood, urine,spinal fluid, and the like can be evaluated for the presence or absenceof bacteria, fungi, viruses, and the like. The particle size, and,optionally, particle shape, can also provide information about thespecific type of bacteria, fungi or virus.

In one embodiment, suitable information on the particles can be obtainedsimply by obtaining a spectra using focused light scattering of a samplemedium, wherein the particle size and distribution provides sufficientinformation about the presence or absence of certain biologicalparticles present in the sample medium. For example, specific bacteria,fungi, or viruses can be identified solely on the basis of their size,and liposomal suspensions can be evaluated for agglomeration solely onthe basis of the size of the agglomerated particles.

In other embodiments, where there is an interest in determining whethera particular agent forms a complex with a particular type of biologicalparticle, additional information may be required. That is, one candetermine the presence or absence of a particular cell type, or anejected particle from a type of cell, by forming a complex between a)the cell or ejected particle and b) an active agent conjugated to amicroparticle or nanoparticle (“conjugate”). The complex has a largerparticle size than the cell, the ejected particle, or the conjugate, sothe focused light scattering technique can determine whether a complexwas formed.

In some aspects of this embodiment, the biological particle is a cellthat expresses a specific receptor, and the techniques permit highthroughput screening of putative therapeutic agents that bind to thereceptor.

In other aspects of this embodiment, the biological particle comprisescells from a patient, for example, blood cells or cancer cells, andthese cells are incubated with putative therapeutic agents. Agents thatbind to the cells can potentially be useful as therapeutic agents forthe patient. Accordingly, this embodiment provides personalized medicineapproaches.

In some of these embodiments, two spectra are taken. The first is takenon the sample media before complex formation, and the second is takenafter complex formation, so one can look for the difference in particlesize and distribution. However, in other embodiments, where the complexhas a known particle size, and all that is required is to show that thecomplex formed, one can simply incubate the biological particle and thesubstance which may or may not form a complex with the biologicalparticle, and use focused light scattering techniques to determinewhether the complex was formed.

If the sample medium, with the biological particle and the conjugateboth present, is passed repeatedly through the focused light scatteringdetector over a period of time, the kinetics of complex formation can beobserved.

If the sample medium is scanned with the biological particle and theconjugate both present, but with different scans taken with differingconcentrations of the biological particle and/or conjugate, one candetermine additional information, relative to binding affinity, minimuminhibitory concentration, and the like.

If the sample medium includes cells of different sizes, expressingdifferent receptors, then information on the selectivity of a putativetherapeutic agent for one receptor over the other can be obtained.

If the agent binding to the cells results in cell rupture, then theefficacy of the active agent can be represented by a decrease inparticle (cell) density in the sample medium over time.

Thus, complex formation provides useful information about the biologicalparticle, or the agent bound to the microparticle or nanoparticle. Forexample, where the cell is a known cell, one can screen putativetherapeutic agents for their ability to bind to the cell. Where thetherapeutic agent is a known therapeutic agent, one can determinewhether a particular cell binds to the therapeutic agent. Thisinformation can be useful in identifying personalized medical approachesfor a patient.

For example, it is critical to determine in a timely manner whether acancer patient will respond to a particular therapy. That is, the tumorscan grow and metastasize before the physician determines that thepatient does not respond to the therapy.

In another example, a small percentage of patients in need of a druglike clopidogrel bisulfate are unable to use clopidogrel bisulfate,because their blood cells do not bind to it. While one could screen theblood cells for a particular genetic variation, genetic testing isexpensive and time consuming. Here, the patient's blood cells can beincubated with clopidogrel bisulfate, and one can quickly determinewhether the patient will respond to this type of therapy. Sinceplatelets will clump if they do not bind to and interact with theclopidogrel bisulfate, the clopidogrel bisulfate need not be conjugatedto a microparticle. That is, one can determine whether a patient willrespond to treatment by looking for platelet aggregation. However, ifthe biological particle of interest will not significantly change itssize (i.e., gain or lose size) during the screening assay, then it maybe necessary to conjugate a putative therapeutic agent to amicroparticle.

In one embodiment, the microparticles have a particle size in the rangeof between about 0.1 and 10 μm, and ideally have a relatively consistentamount of active agent bound to them. One way to produce particles witha relatively consistent amount of active agent bound to them is to usedendrimers, where the dendrimers include a known quantity of the activeagent. Another way is to produce polymer particles with a) a relativelynarrow size distribution, and b) a relatively consistent amount ofprotected functional groups, so that after the polymers are produced,the protecting groups can be removed, and the functional groups used toconjugate the polymer particles to an active agent.

The active agent can be conjugated with the particle in such a way thatthe portion of the active agent that is known to be active (i.e., bindsa receptor) is not significantly sterically hindered by its conjugationwith the particle. In some embodiments, this will involve preparing ananalogue of the active agent which includes a further functional groupwhich can be attached to the particle.

In one embodiment, metallic particles, such as gold particles, are used.Because these particles scatter a significant amount of light, they canbe conjugated with a specific active agent, and used to identify evensmall molecules that bind to the agent. That is, the amount of lightthat the particle scatters is sufficiently large that the binding of theagent to the molecule of interest can be measured, even though themolecule is not within the size range of biological particles that canbe measured. Means for conjugating active agents to metallic particlesare known to those of skill in the art.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a simplified block diagram of the LE-type sensor of thepresent invention, hereinafter the “new LE-type sensor,” using arelatively narrow, focused light beam to illuminate particles flowing ina relatively thin flow channel;

FIG. 2 is a simplified block diagram of the LS-type sensor describedherein, using a relatively narrow, focused light beam to illuminateparticles flowing in a relatively thin flow channel.

FIG. 3 is a block diagram showing a further embodiment of the lightscattering device used in the analytical methods described herein.

FIGS. 4-7 are illustrative graphs showing a group of biologicalparticles, and an antibody coupled to a microparticle, where theantibody/microparticle conjugate binds to biological particles. Timezero is shown in FIG. 3, and as the conjugate binds to the biologicalparticles, the progression of events, including lowering of theconcentration of the biological particle and the antibody/microparticleconjugate, and the increase of a peak showing the biological particlelinked to the conjugate, is shown in FIGS. 4-7.

DETAILED DESCRIPTION OF THE INVENTION

The present invention relates to methods for using focused lightscattering techniques in biological applications. Focused lightscattering techniques provide one with the ability to analyze a fluidand determine the size and number of particles in a given sample and to,optionally, further characterize the particles in the sample. Where theparticle is a biological particle, this information can be used todiagnose disease, to conduct high throughput bioassays, and to obtaininformation for personalized medical treatment.

The methods described herein provide numerous advantages over theprevious methods in the art, including the ability to identify andcharacterize smaller particles, identify particles and determineparticle size, number or other characteristics without using fluorescentantibodies or expensive flow cytometry, improving the identification ofthe initial onset of the change in voltage due, which would improveresolution of the generated spectra, control of particle shearing, andimproved information regarding particle shape.

The methods also provide numerous characteristics of the particles beingevaluated, including, but not limited to: identifying biologicalparticles and distinguishing them from various cells, quantifyingparticles, identifying surface epitopes, identifying particle shape, andcorrelating this information with platelet activation, thrombinproduction, disease states, and the efficacy of putative therapeuticagents.

DEFINITIONS

The term “cell” as used herein refers to any type of cell, includinghuman cells, animal cells (such as swine cells, rodent cells, caninecells, bovine cells, ovine cells and/or equestrian cells) cloned cells,plant cells, or the like. The cells may be blood cells, cultured cells,biopsied cells, or cells that are fixed with a preservative. The cellscan be nucleated, such as white blood cells or suspended endothelialcells, or non-nucleated, such as platelets or red blood cells.

The term “focused light scattering” refers to a method for sensingsingle particles, suspended in a solution, when the solution is passedthrough a focused beam. When the beam passes through the solutionwithout being scattered by a particle, the beam passes on to aphotodetector and the intensity is measured. When the beam is scattered,in whole or in part, by a particle, the intensity of the beam hittingthe photodetector is altered. The particle size and concentration can becalculated, for example, using light-extinction, light-scatteringdetection, or both.

A “focused light scattering device” is a multi-particle optical sensor,which has high sensitivity and responds to relatively concentratedsuspensions, uses a relatively narrow light beam to illuminate anoptical sensing zone non-uniformly.

As used herein “particles” are small fragments or completely intactbiological cells, and related to a living organism when referred to as“biological particles.” Intact cells may range in size from about 1micron to 20 microns. Aggregates of intact cells or fragments of cellsmay range in size from 2 microns to 100 microns. “Microparticles” arefragments of biological cells or particles that generally range in sizefrom about 0.1 μm to about 0.8 μm, generally 0.1-20 μm. Examplesinclude, but are not limited to blood cells, platelets (1-3 micron),cancer cells (5-15 micron), red blood cells (˜7 μm), white blood cells(˜5-10 μm), bacteria (˜0.5-1 μm), tumors, granulocytes, monocytes,neutrophils, lymphocytes, endothelial cells, stem cells, viruses, andfungi.

“Light extinction” as used herein is a measurement of the absorptionand/or scattering of light in an electromagnetic field by particles asthey pass through the field. As a particle passes through a field, thereis a momentary reduction in the transmitted light intensity due to thelight refraction, absorption and/or scattering. Measurement of lightextinction by the particles provides additional information regardingthe characteristics of the particles. A light extinction spectrum can begenerated for each particle. An exemplary light extinction system isillustrated in FIG. 1-3.

“Light scattering” occurs when there is a momentary change in theintensity of the incident light caused by the interaction of theincident photons with the particle. In the case on focused scatteringdevice, the intensity of the scattered light reaching the detector isproportional to the size of the particle. Thus, when the particles beingcharacterized are biological particles, the method of light scatteringwill involve measuring voltage at the detector this will be proportionalto the particle size. Exemplary focused light scattering systems fordetecting biological particles are shown in FIGS. 1-3.

“Nanoparticles” as used herein are particles or biological particlesthat are generally smaller than 0.1 μm in size. Because of their smallsize, nanoparticles have a very high surface area to volume ratio.Accordingly, nanoparticles often possess unique physicalcharacteristics.

The present invention provides a way to both quantify and monitornanoparticles, in particular, cellular nanoparticles, which are oftenbelieved to be responsible for initiating further biochemical processesin living organisms.

I. Focused Light Scattering Devices and Algorithms for MeasuringParticle Size and Shape

The principal defining characteristic of the focused light scatteringmethod described in U.S. Patent Publication No. 20070010974, thecontents of which are hereby incorporated by reference, is not simply asignificant reduction in the size of the illuminated area, A₀, resultingin a significant reduction in V_(OSZ) and improvement in sensitivity.Rather, it concerns the nature of the illuminating beam and theresulting OSZ thereby defined.

An exemplary apparatus useful for performing the methods describedherein is disclosed in U.S. Patent Application Publication No.20040011975, the contents of which are hereby incorporated by referencein its entirety. The apparatus is described therein is useful inperforming particle analysis using focused light scattering techniques.However, as described herein, other similar apparatus can be employed,including detectors for focused light scattering and/or lightextinction.

The term “focused light scattering” refers to a method for sensingsingle particles, suspended in a solution, when the solution is passedthrough a focused beam. When the beam passes through the solutionwithout being scattered by a particle, the beam passes on to aphotodetector and the intensity is measured. When the beam is scattered,in whole or in part, by a particle, the intensity of the beam hittingthe photodetector is altered. The particle size and concentration can becalculated, for example, using light-extinction, light-scatteringdetection, or both.

A “focused light scattering device” is a single-particle optical sensor,which has high sensitivity and responds to relatively concentratedsuspensions, uses a relatively narrow light beam to illuminate anoptical sensing zone non-uniformly. It differs from conventional SPOSdevices in that it can handle more concentrated solutions and smallerparticle sizes.

In use, a solution including suspended particles passes through a zone.The zone is smaller than the flow channel, so that the sensor respondsto only a fraction of the total number of particles flowing through thechannel, detecting a statistically significant number of particles ofany relevant diameter.

Because different particle trajectories flow through different parts ofthe zone illuminated at different intensities, it is necessary todeconvolute the result. Two methods of deconvolution can be used:modified matrix inversion or successive subtraction. Both methods use afew basis vectors measured empirically or computed from a theoreticalmodel, and the remaining basis vectors are derived from these few. Thesensor is compensated for turbidity.

The sensor apparatus for single-particle optical sizing of particles ina fluid suspension typically includes a means for establishing flow ofthe suspension through a physically well-defined measurement flowchannel. There is also an illumination means for effectively directing arelatively narrow beam of light, having an axis, through the measurementflow channel to form an optical sensing zone within the measurement flowchannel. The beam of light and the optical sensing zone are of such sizerelative to the size of the measurement flow channel that the sensorapparatus responds to only a fraction of the total number of particlesflowing through the measurement flow channel. In this manner, the sensorapparatus responds effectively to a relatively concentrated fluidsuspension.

The beam has a maximum intensity portion and a continuum of lesserintensities for positions spaced transverse to the axis from the maximumintensity portion. In this manner, some of the particles havetrajectories through the maximum intensity portion, others of theparticles have trajectories through the lesser intensity positions, andstill others of the particles may have trajectories outside the zone.Typically, the maximum intensity portion of the beam is in a centralportion of the beam.

The device also includes a detector means for photo-detecting light fromthe zone to provide pulse height signals. These signals each respond toa particle flowing through the zone. The pulse height signals arefunctions of the sizes and trajectories of detected particles. Particlesof a given size provide a maximum pulse height signal when flowingthrough the maximum intensity portion, and lesser pulse height signalswhen flowing through the lesser intensity positions of the zone. Thepulse height signals, collectively, form a pulse height distributionPHD.

The device further includes a means for mathematically deconvoluting thepulse height distribution to extract a particle size distribution of thePSD particles in the fluid suspension. The sensor apparatus can detect astatistically significant number of particles of any given diameter orrange of diameters that are relevant to the fluid suspension.

In one embodiment, the measurement flow channel has a thicknessdimension axially of the beam of light, a width dimension transverse tothe beam, and a flow direction substantially perpendicular to thethickness and width dimensions. The beam is narrower than themeasurement flow channel in the width direction. The beam can be focusedwith a depth of field which is substantially larger than the thicknessdimension, and the beam substantially has an effective width which doesnot vary substantially over the thickness dimension.

In another embodiment, the beam has an effective width between opposingpositions transverse to the axis in the beam, at which the lesserintensities have fallen to a given fraction of the maximum intensity.The effective width is chosen so that the largest particles of interestcan be effectively sized. The given fraction can be, for example, 1/e²of the maximum intensity, where e is the base of the natural system oflogarithms, and the effective width is substantially one half the sizeof the largest particle to be sized.

The light beam can have, for example, a Gaussian intensity profile, acircular cross-section, or an elliptical cross-section being wider in adirection transverse to particle flow.

The detector means can be include a light extinction-type detector, andcan be a combination of detectors, for example, a light-extinctiondetector type and a light-scattering type detector. The light-scatteringtype detector means can include means for passing a portion of scatteredlight from the zone through a mask to select light scattered between afirst and a second angle to the beam and a means for directing a portionof the light transmitted through the zone to a light-extinction typedetector.

The detector means can include a mirror for deflecting a portion of thelight from the optical-sensing zone to the light-extinction detector.The illuminating means can include a light source and optical fibermeans for conveying light from the light source to the optical sensingzone, and projecting the light through the zone.

The detector means can also include an optical fiber means for conveyingthe light passing through the optical sensing zone to thelight-extinction type detector. The detector means can also includemeans for passing a portion of the light scattered from the zone througha mask, to select light scattered between a first and second angle tothe beam, and an optical fiber means for conveying the portion of thelight to a light-scattering type detector. The detector means can alsoinclude a light-scattering detector.

In one embodiment, the illumination means provides two light beamsdirected through a pair of optical sensing zones positioned within themeasuring flow channel, and each beam has an effective width determinedby a desired maximum particle size.

The detector means can include a light-scattering detector and a meansfor passing light scattered from the zone through a mask means. The maskmeans can include a plurality of masks and means for selecting one ofthe masks for passing the light scattered from the zone, each maskdefining different angles between which the light is scattered. Themasks can be located on a rotatable wheel, and a mask can be selected byrotating the wheel to a desired position.

The illuminating means can project a relatively wide collimated beamthrough the optical sensing zone, and can include an acceptance apertureto capture only those light rays that closely surround the axis of thebeam. This reduces the effective width of the beam to a width in adirection transverse to the axis of the light beam which issubstantially one-half the size of the largest particle to be sized. Theilluminating means can also include a means for coupling the light raysto the detector means. This can be, for example, an optical fiber means.

In one aspect of the invention, a statistically significant number ofparticles of each relevant size flow through all portions and positionsof the zone.

In another aspect of the invention, the fluid suspension is relativelyconcentrated and the apparatus further comprises means to compensate forturbidity of the suspension. In this aspect, the detector means canoperate on a light extinction principle, and provide a signal having abaseline voltage level. The pulse height signals appear as downwardlyextending pulses from the baseline voltage level, and the means forcompensation for turbidity of the suspension can include means to sensethe baseline voltage level and automatically increase the level toapproximately the baseline voltage level present in the absence ofturbidity in the suspension. The detector means can operate on a lightextinction principle, and provide a signal having a baseline voltagelevel, wherein the means to compensate for turbidity can include acomputer means for correcting the pulse height signals in response tothe ratio of the baseline voltage level when the fluid suspension is notturbid, to the baseline voltage level for the turbid fluid suspension.

The detector means can also operate on a light extinction principle andprovide a signal having a baseline voltage level, wherein the means tocompensate for turbidity includes a means to adjust the intensity of thebeam of light by increasing the amount of light produced by theilluminating means in response to the ratio of the baseline voltagelevel when the fluid suspension is not turbid, to the baseline voltagelevel for the turbid fluid suspension.

The particle trajectories can be substantially uniformly distributedacross the width of the measurement flow channel.

The means for deconvoluting the pulse height distribution can includebasis vectors, each corresponding to a particular particle size, and asource vector representing a measured pulse height distribution for afluid suspension as detected by the detector means. There can also be ameans using a deconvolution algorithm to derive the particle sizedistribution from the pulse height distribution. At least some of thebasis vectors can have values based upon measurements of particles ofknown size. Some of the basis vectors can also have values based uponmeasurements of particles of known size and others of the basis vectorscan be computed from the sum of the basis vectors by interpolationand/or extrapolation.

The basis vectors can be computed, and the basis vectors can be columnbasis vectors of a matrix, where the means using a deconvolutionalgorithm performs matrix inversion and vector multiplication, or themeans using a deconvolution algorithm can perform successivesubtraction.

The means using a deconvolution algorithm can provide a deconvolutedpulse height distribution dPHD, and the apparatus further comprisesmeans providing a calibration curve of the relationship of pulse heightand diameter, and means using the calibration curve to transform eachdeconvoluted pulse height value in the dPHD into a unique particlediameter associated with this pulse height value. This can yield a “raw”particle size distribution PSD. There can also be a means for convertingthe raw PSD into a final PSD by renormalizing the raw PSD by multiplyingby the value 1/PHI_(d), where PHI_(d) is the fraction of particlesactually detected by the device for particles of each size.

The particle trajectories can be distributed non-uniformly across thewidth of the measurement flow channel, and the basis vectors can bebased upon the response of particles of known size flowing through themeasurement flow channel with the same non-uniform distribution ofparticle trajectories as the fluid suspension.

The sensor apparatus may respond only to a fraction of the total numberof particles flowing through the measurement flow channel.

One can prepare a matrix for deconvoluting pulse height distributionsderived from particles of unknown size flowing along differenttrajectories through a non-uniform light field of a single-particleoptical sizing device. This can enable one to size particles in a fluidsuspension. To do this, one can determine the value of at least oneempirical basis vector for the matrix by measuring the response ofparticles of known size flowing through the single-particle opticalsizing device. Then, one can compute other basis vectors for the matrixcorresponding to particles of other sizes, by interpolating and/orextrapolating the other basis vectors from the empirical basis vector.

One can also determine the value of additional empirical basis vectorsfor the matrix by measuring the response of particles of known sizesflowing through the single-particle optical sizing device, and computingthe other basis vectors for the matrix corresponding to particles ofother sizes from the at least one empirical basis vector and theadditional empirical basis vectors.

Another way to prepare a matrix for deconvoluting pulse heightdistributions derived from particles of unknown size flowing alongdifferent trajectories through a non-uniform light field of asingle-particle optical sizing device for sizing particles in a fluidsuspension involves determining the value of at least one computed basisvector corresponding to particles of at least one size for the matrix.One can compute other basis vectors for the matrix corresponding toparticles of other sizes from computed basis vectors.

Also disclosed is a method of deconvoluting a pulse height distributionderived from particles of unknown size flowing along differenttrajectories through a non-uniform light field of a single-particleoptical sizing device for sizing particles in a fluid suspension. Themethod involves setting up a matrix having a plurality of columns, eachcontaining a basis vector comprising a pulse height distribution ofparticles of a known size corresponding to the response of aphoto-detector of the device to the particles of known size. Eachsuccessive column contains a basis vector for particles of successivelylarger sizes. The matrix also has a like plurality of rows, eachcorresponding to a successive pulse height channel, each channelincluding a range of pulse heights, with successive rows correspondingto successively larger pulse heights, and with each column having amaximum count pulse height value at a location for a row which relatesto a pulse height corresponding to the particle of known size associatedwith the column. The maximum count pulse height values for successivecolumns are arranged on a diagonal of the matrix. The matrix is modifiedby setting all terms corresponding to pulse height values greater thanthe maximum count pulse height value in a column to zero. Adeconvolution algorithm is used to perform matrix inversion and vectormultiplication of the pulse height distribution and the matrix asmodified.

Before the modifying step, one can renormalize the values of the basisvectors in the columns by setting the maximum count pulse height valueto equal 1.0 and all other count pulse height values in the column to avalue maintaining the same proportionate value to 1.0 that the othercount pulse height values had to the maximum count pulse height value ofthe column.

The response of the photo-detection to the particles of known size isdeveloped empirically for some of the basis vectors by sending particlesof the substantially known size through the device and providing aresponse by the device to the particles of known size. The response tothe photo-detector for the remaining basis vectors can be computed byinterpolating and/or extrapolating the response for the remaining basisvectors from the some of basis vectors.

The response of the photo-detector to the particles of known size can becomputed for some of the basis vectors and the response to thephoto-detector for the remaining basis vectors can be computed byinterpolating and/or extrapolating the response from the some basisvectors.

A pulse height distribution (“PHD”) can be derived from particles ofunknown size flowing along different trajectories through a non-uniformlight field of a single-particle optical sizing device for sizingparticles in a fluid suspension can be deconvoluted by setting up amatrix having a plurality of columns. Each column includes a basisvector comprising a pulse height distribution of particles of asubstantially known size corresponding to the response of aphoto-detector of the device to the particles of known size, and eachsuccessive column contains a basis vector for particles of successivelylarger sizes. The matrix can also include a like plurality of rows, eachcorresponding to a successive pulse height channel, each channelincluding a range of pulse heights, successive rows corresponding tosuccessively larger pulse heights, each column having a maximum countpulse height value at a location for a row which relates to a pulseheight corresponding to the particle of known size associates with thecolumn. The maximum count pulse height values for successive columns canbe arranged on a diagonal of the matrix. A successive subtractionalgorithm can be implemented, by starting with the basis vector with itsmaximum count value in the largest row number; scaling a column basisvector by a factor corresponding to the value of the row in the PHD thatmatches the column number; subtracting the scaled basis vector from thePHD to form an element of a deconvoluted PHD (dPHD), leaving anintermediate PHD vector with a smaller number of total particles; andrepeating this process using the remaining basis vectors until theentire PHD has been consumed and all the elements of the deconvoluteddPHD have been formed.

A single-particle optical sizing sensor for sizing particles in arelatively concentrated fluid suspension sample for turbidity of thesuspension sample can be compensated using a sensor operating on a lightextinction principle whereby a photo-detector produces signal V_(LE)(t)having a baseline voltage level and a response to blockage of light by aparticle as a downwardly extending pulse from the baseline voltagelevel. The compensation method involves passing a non-turbid suspensionthrough the sensor; measuring a baseline voltage level V₀ produced inresponse to the non-turbid suspension; passing the relativelyconcentrated suspension sample through the sensor; measuring a baselinevoltage V₀ ^(T) produced in response to the relatively concentratedsuspension sample, calculating the ratio 1 G=V 0 V 0 T; and adjustingthe sensor in response to G to compensate for the turbidity when therelatively concentrated suspension sample passes through the sensor.

The baseline voltage V₀ ^(T) can effectively be subtracted from thesignal V_(LE)(t), the remaining signal can be inverted to produce apulse height signal 2 V LE T (t), and an adjustable gain amplifyingmeans can be used to amplify the pulse height signal 3 V LE T (t). Theadjustable gain amplifying means can be controlled by the ratio G toprovide a compensated pulse height signal ΔV_(LE(t)).

The signal V_(LE(t)) produced by the sensor in response to therelatively concentrated suspension sample can be amplified by adjustablegain amplifier means, the gain of which is controlled by the ratio G toprovide a compensated signal V_(LE(t)) having a compensated baselinevoltage V₀, subtracting the baseline voltage V₀ from the compensatedsignal V_(LE(t)), and inverting the remaining signal to producecompensated pulse height signal ΔV_(LE(t)).

In one embodiment, the single-particle optical sizing sensor comprises alight source producing a light beam of adjustable intensity, wherein theintensity is increased in response to the ratio G to compensate for theturbidity.

Particles in a fluid suspension can also be optically sized byestablishing a flow of the suspension through a physically well-definedmeasurement flow channel of a single-particle optical sizing sensorapparatus wherein a beam of light, having an axis, is directed throughthe measurement flow channel to form an optical sensing zone within themeasurement flow channel. The beam of light and the optical sensing zoneare ideally of such size relative to the size of the measurement flowchannel that the sensor apparatus responds to only a fraction of thetotal number of particles flowing through the measurement flow channel.The sensor apparatus can respond effectively to a relativelyconcentrated fluid suspension. The beam can have a maximum intensityportion in the beam and a continuum of lesser intensities for positionsin the beam spaced transversely from the axis, whereby some of theparticles have a trajectory through the maximum intensity portion,others of the particles have trajectories through the lesser intensitypositions, and still others of the particles may have trajectoriesoutside the zone. Light from the zone can be detected to provide pulseheight signals, each responsive to a particle flowing through the zone.The pulse height signals are functions of the sizes and trajectories ofdetected particles, and the pulse height signals collectively form apulse height distribution PHD. The PDH can be mathematicallydeconvoluted and processed to extract from the PHD a particle sizedistribution PSD of the particles in the fluid suspension.

The step of mathematically deconvoluting the PHD can involve determiningthe value of at least one empirical basis vector by measuring theresponse to particles of known size flowing through the single-particleoptical sizing device. Other basis vectors corresponding to particles ofother sizes can be computed by interpolating and/or extrapolating theother basis vectors from the empirical basis vector.

The value of additional empirical basis vectors for particles of knownsizes flowing through the single-particle optical sizing device can bedetermined; and the other basis vectors for the matrix corresponding toparticles of other sizes can be calculated by interpolating and/orextrapolating the other basis vectors from at least one empirical basisvector and the additional empirical basis vectors. The method canfurther involve determining the value of at least one computed basisvector corresponding to particles of at least one size. Other basisvectors corresponding to particles of other sizes can also be computedby interpolating and/or extrapolating the other basis vectors fromcomputed basis vectors.

The step of deconvoluting and processing the PHD can involve setting upa matrix having a plurality of columns, each containing a basis vectorcomprising a pulse height distribution of particles of a known sizecorresponding to the response of a photo-detector of the device to theparticles of known size, each successive column containing a basisvector for particles of successively larger sizes. The matrix can alsohave a like plurality of rows, each corresponding to a successive pulseheight channel, each channel including a range of pulse heights,successive rows corresponding to successively larger pulse heights, eachcolumn having a maximum count pulse height value at a location for a rowwhich relates to pulse heights corresponding to the particle of knownsize associated with the column. The maximum count pulse height valuesfor successive columns can be arranged on a diagonal of the matrix. Thematrix can be modified by setting all terms corresponding to pulseheight values greater than the maximum count pulse height value in acolumn to zero. A deconvolution algorithm can be used to perform matrixinversion and vector multiplication of the pulse height distribution andthe inverted matrix as modified. The response of the photo-detector tothe particles of known size can be developed empirically for some of thebasis vectors by directing a flow of particles of the known size throughthe device and providing a response by the device to the particles ofknown size. The response to the photo-detector for the remaining basisvectors can be calculated by interpolating and/or extrapolating theresponse for the remaining basis vectors from the some of basis vectors.

The step of mathematically deconvoluting the PHD can also involve usinga deconvolution algorithm to provide a deconvoluted pulse heightdistribution dPHD. The method can further involve providing acalibration curve of the relationship of pulse height and diameter, andusing the calibration curve to translate each deconvoluted pulse heightvalue in the dPHD into a unique particle diameter associated with thispulse height value yielding a “raw” particle size distribution in PSD.The raw PSD can be converted into a final PSD by renormalizing the rawPSD by multiplying by the value 1/PHI_(d), where PHI_(d) is the fractionof particles actually detected by the device for particles of each size.

Representative focused light scattering devices are shown in FIGS. 1-3.

As is shown in FIG. 1, there are two important features inherent in theoptical design. First, the incident beam alone (in conjunction with thefront and back windows 36 and 37 of the measurement flow channel 35)defines the OSZ. The side walls 38 and 39 that confine thefluid-particle suspension along the x-axis are no longer of anyconsequence with respect to definition of the OSZ. Second, the physicalvolume associated with the OSZ can no longer be described by a singlevalue; rather, it now depends on the size of the particles beingmeasured.

The approach, shown schematically in FIG. 1, is to illuminatemeasurement flow channel 35 with a light beam 41 from a laser lightsource 40 which is focused by a lens 42 to form a beam 44 of relativelynarrow cross section—i.e., smaller than. a typical illuminated width, a,of the flow cell in a conventional LE-type sensor. The resulting OSZ istherefore defined approximately by a “pencil” beam of light 46, togetherwith the front and back windows of the flow cell, separated by dimension“b.” The schematic diagram in FIG. 1 provides a simplified picture ofthe OSZ defined by focused light beam 46. First, the region ofillumination that comprises the OSZ is not sharply defined, as impliedby the approximately cylindrical zone indicated in FIG. 1. Rather, theouter boundary of the OSZ is “fuzzy,” extending well beyond the zoneindicated, as discussed below. Second, the beam passing through the flowchannel 10, assuming that it has been focused, is typically is notuniform in width. Rather, in the case of a focused beam, its widthvaries over the depth of the measurement flow cell 35. The extent towhich the beam waist varies over the depth of the channel depends on thedepth of field of the focused beam, defined as the distance (y-axis)between the points at which the beam waist grows to 2 times its minimumvalue. Ideally, the depth of field is significantly greater than thechannel thickness, b, resulting in a relatively uniform beam widththroughout the flow channel.

Consequently, focused light scattering devices may include afundamentally different sensor. In the conventional design, the physicalwidth of the flow channel 10 and the effective width (x-axis) of the OSZare one and the same, equal to dimension “a.” By contrast, the physicalwidth of the flow channel in a sensor used for focused light scatteringdevices (also defined as “a”) is typically much larger than the nominalwidth, 2w, of the incident light beam and therefore has no significantinfluence on the OSZ. Hence, the spacers (or shims) 38 and 39 thatseparate the front and back windows 36 and 37, determining the depth, b,of the flow cell (and OSZ), no longer need to be opaque or smooth on anoptical scale to avoid scattering by the edges. This is a significantadvantage, making fabrication of the flow cell easier and lessexpensive.

It is usually convenient and effective to employ a “circularized” lightbeam, in which the incident intensity ideally depends only on the radialdistance, r, from the beam axis (coincident with the y-axis, with x=z=0,as seen in FIG. 1). Typically, one employs a “gaussian” light beam—i.e.one having a gaussian intensity profile, described in the focal plane(minimum beam waist), at y=b/2, by I(r)=I₀exp(−2r²/w²)(7) where r²=x²+z²for the assumed circular beam.

Quantity 2 w is the diameter of an imaginary cylinder containing most ofthe incident light flux. The intensity on its surface equals 1/e², wheree is the base for natural logarithms, or 0.135 times its value, I⁰, atthe center of the beam (r=0). Essentially 100% (apart from losses due toreflections at optical interfaces and extinction by particles in thebeam) of the light flux contained in the incident beam traverses thefluid-particle mixture in the flow channel and impinges on the distantdetector D_(LE). This causes detector D_(LE) to provide a lightextinction signal V_(LE) in the form of a downwardly extending pulse,resembling pulse 30 in FIG. 2 at the output of I/V converter amplifier34.

This behavior is in sharp contrast to the illumination scheme employedin a conventional LE-type sensor. There, the starting light beam isexpanded greatly along the lateral (x) axis of the flow cell, so thatits width (1/e² intensity) is much larger than the width, a, of thefront window (and OSZ). As a result, there is relatively littlevariation in the incident intensity along the x-axis (i.e. for y=z=0)where the beam enters the flow cell, because the light is captured atthe top of the x-expanded gaussian beam. Therefore, a particle passingthrough the OSZ will experience substantially the same maximum beamintensity (i.e. at z=0), regardless of its trajectory. The specificvalues of x and y defining the trajectory ideally have no influence onthe resulting sensor response, i.e. the pulse height.

There is a sharp contrast between the conventional optical design andthe scheme employed in the sensor used for focused light scatteringdevices. There is a large variation in the incident intensity as afunction of position (x-axis) across the width of the flow channel. Inthe case in which the incident light beam has a symmetric (circular)gaussian profile, the intensity variation is given by Equation 7, withr=x. The maximum intensity, I₀, is achieved at the center of the beam(x==0), where for simplicity x=0 represents the midpoint of the channel(with the side walls at x=±a/2). As noted, the intensity occurring atx=±w, z=0 is reduced substantially, to 0.135 I₀. The intensity dropssteeply with increasing distance from the beam, falling, for example, to0.018 I₀ at x=±2w, z=0 and 0.00033 I₀ at x=±4 w, z=0.

The consequences for the light-extinction signal thus generated by thepassage of particles through the new OSZ are far-reaching. First, as fora conventional LE-type sensor, the pulse height, ΔV_(LE), generated bypassage of a particle through the OSZ in general increases withincreasing particle size, all other factors being equal. In general, thelarger the particle, the larger the fraction of light “removed” from theincident beam, thus unable to reach the detector D_(LE). However, withthe new sensor the fraction of light removed from the beam now dependson the precise trajectory of the particle—specifically, the minimumdistance, |x|, of the particle to the center of the beam, x=0. (To firstapproximation, the response of the sensor will not vary significantlywith changes in the y-axis value of the trajectory, assuming that thebeam width is approximately constant over the depth of the flow channel,given an appropriately large depth of field, as discussed above.)

For a particle of given size and composition (hereinafter assumed to bespherical and homogeneous, for simplicity), the maximum “signal,” orpulse height, is achieved when the particle passes through the center ofthe beam, x=0. A particle of given effective cross-sectional area, ΔA,blocks the largest amount of incident light at the center of the beam,where the intensity is greatest. Particles of identical size that passthrough the flow channel along different trajectories, with differentminimum distances, |x|, from the beam axis, are exposed to varying, butsmaller, maximum levels of illumination. The greater the distance fromthe beam axis, the lower the integrated intensity incident on a particleand, hence, the less light flux removed from the beam, and the smallerthe resulting pulse height. The response therefore consists of acontinuous “spectrum” of pulse heights, ranging from a maximum value,for trajectories that pass through the center of the beam, toessentially zero (i.e. indistinguishable from noise fluctuations), fortrajectories located very far from the incident beam (|x|>>w). Themaximum pulse height depends on the beam waist, 2w, and the size of theparticles, as well as in some cases the refractive indices of theparticles and surrounding fluid. (This depends on the extent to whichlight scattering is significant relative to refraction and reflection incontributing to the overall light extinction signal.) A crucialassumption is that the particle trajectories are distributed randomly(i.e. occur with equal frequency) within the flow channel. Thisassumption is usually valid, given the typical dimensions of the flowchannel and the relatively low flow rates utilized. It is also assumedthat the number of particles passing through the sensor is sufficientlylarge that the statistical fluctuations in the number of particleshaving trajectories with any given x-axis value (i.e. over any (narrow)range of x values) can be ignored.

The relationship between particle size and pulse height for the sensorin a focused light scattering device is therefore radically differentfrom that obtained for a sensor of conventional design. In the lattercase, particles of a given size (and composition) give rise to pulses ofnearly uniform height, irrespective of their trajectories. This behavioris important for sensor design for the conventional SPOS method. Thetypically small variations in pulse height that occur, for example, whenmeasuring polystyrene latex “standard” particles of essentially uniformsize are caused by variations in the incident beam intensity within theOSZ along the x- and y-axes, for a given z-axis value. These variationsultimately determine the resolution of the sensor. The resulting widthof the PSD is therefore mostly a consequence of residual non-uniformityof illumination across the OSZ, rather than an actual range of particlediameters.

By contrast, there is an obvious deterioration in the particle sizeresolution for sensor design for focused light scattering devices. Whena single particle passes through the sensor, it gives rise to alight-extinction pulse with a height, ΔV_(LE) that can vary between agiven maximum value and essentially zero. Conversely, given a singledetected pulse, it is impossible to determine the size of the particlethat has produced it, solely from knowledge of the pulse height. Forexample, a particle that is relatively small, but which passes directlythrough the beam axis, yields the maximum pulse height possible for aparticle of that size (and composition). Alternatively, a particle thatis much larger but which passes relatively far from the beam axis yieldsa pulse height that could actually be the same, depending on its sizeand trajectory. Even though the large particle is able to intercept amuch larger area of incident illumination than the small one, theaverage intensity incident on it is smaller than the intensity incidenton the small particle. Hence, the resulting pulse height could turn outto be the same as that produced by the small particle. Obviously, thereare an infinite number of pairs, {d, |x|}, of particle diameters andminimum beam-trajectory distances that can give rise to the same pulseheight. The particle diameter, d, and the resulting pulse height,ΔV_(LE), are effectively “decoupled” from each other. This is theproblem of “trajectory ambiguity”, which for more than twenty years hasmotivated the search for new light-scattering based schemes for particlesize determination using gaussian beams.

The effects of trajectory ambiguity described above might present adifficulty in measuring the size of a single particle, or a relativelysmall number of particles. However, the apparently poor size resolutionassociated with the sensor used for focused light scattering devices canbe restored to a very acceptable level by means of appropriatemathematical deconvolution of the pulse-height data. The resultingdramatic improvement in the effective sensor resolution is possible byvirtue of the fact that the sensor in a focused light scattering deviceis intended to be exposed to a large, statistically significant numberof particles of every relevant diameter, or range of diameters,contained in the sample of interest. This is the circumstance thatrenders the new sensing method very useful for particle size analysis,in sharp contrast to the situation that holds for “contamination”applications. There, the sensor is exposed to relatively small numbersof particles of any given size, for which statistical significance isoften not achieved.

The “raw” response of the sensor used in a focused-beam device, like itsconventional SPOS predecessor, consists of the pulse height distribution(PHD) —a histogram of particle “counts” vs pulse height, ΔV_(LE). Thepulse-height scale is typically divided into a relatively large number(e.g. 32, 64 or 128) of “channels,” or “bins,” each of which encompassesan appropriately narrow range of pulse height voltages, thus definingthe voltage resolution of the PH). It is usually convenient to establishchannels that are evenly spaced on a logarithmic voltage scale.Measurement of a new pulse causes the number of particle counts storedin the appropriate pulse height channel in the histogram to beincremented by one. Data are ideally collected from the particlesuspension of interest for a sufficiently long time that the resultingPHD becomes statistically reliable, and thus smooth and reproducible.This means that the number, N_(I), of particle counts collected in theI-th pulse-height channel is statistically significant, dominating thefluctuations due to statistical “noise,” for all I, e.g. for 1≦I≦128, inthe case of 128 channels. Assuming Poisson statistics, this means thatN_(I)>>N_(I), for all I.

Relatively high levels of particle concentration are possible becausethe sensor responds to only a small fraction of the total number ofparticles passing through it. For example, concentrations in the rangeof hundreds of thousands of particles/ml, in sample sizes of tens ofmls, can be measured. That is, millions of particles can be present, aportion of which is passed through the beam of light and counted. Thefraction of particles that are actually counted, relative to the numberof particles present in the sample (Np), is known as phi_(d), or “sensorefficiency,” and is calculated by taking the ratio of the particlesactually detected over the number of particles in the sample. The numberof particles detected over the number of particles in the sampletypically ranges from about 0.5 to about 5%.

The fact that the sensor efficiency is so relatively small is notsurprising. In the case of a tightly focused beam, the width, a, of theflow channel is invariably much larger than the nominal width, 2w, ofthe focused beam. Therefore, most of the particles passing through thesensor are exposed to negligible levels of light intensity, becausetheir trajectories are located so relatively far from the beam axis—i.e.|x|>>w. Consequently, only a small fraction of the total number ofparticles are able to “block” enough light to give rise to detectablepulses, relative to the prevailing noise level. The great majority ofparticles pass undetected through the sensor.

While this limitation may appear to be serious, in practice it is oflittle concern, for two reasons. First, the fraction, phi_(d), ofparticles that produce detectable, measurable pulses will be fixed for agiven sensor width, a, even though the value changes with particlediameter, d. Second, the new sensing method is intended for use indetermining the particle size distribution (PSD) for samples that, bydefinition, are highly concentrated to begin with. Even followingdilution, if required, the concentration of particles of any given size(i.e. within any (narrow) size range) is, by definition, relativelyhigh. Assuming a suitable flow rate and data collection time, theresulting PHD will possess an acceptable signal/noise ratio, with a lowlevel of statistical fluctuations. Hence, even though only a smallfraction of the available particles will contribute to the raw data, theresulting PHD will be representative of the much larger number ofparticles in the sample that are ignored. Therefore, a reliable andaccurate PSD, representative of the entire sample, can be obtained fromthe “inefficient” sensor used in the focused light scattering devicesdescribed herein.

Several additional features of the PHD that can be obtained arenoteworthy. First, as a consequence of the fact that the particletrajectories span a large range of 1×1 values, passage of uniformparticles through the sensor indeed results in a PHD containing a widerange of pulse heights. In this case, these range from the threshold ofindividual pulse detection (dictated by the prevailing r.m.s. noiselevel), roughly 5 millivolts (mV), to a maximum of approximately 326 mVfor the nominal “end” of the distribution. (This excludes a small numberof “outlier” pulses, due to agglomerates and over-size primaries thatextend to 500 mV). Given the uniformity of the particles, this 65-foldrange of pulse heights can only be ascribed to differences in particletrajectory. (To a first approximation, one can neglect variations in thebeam width over the depth of the flow channel, as discussed earlier.)

Second, as expected, the PHD is highly asymmetric, skewed greatly in thedirection of smaller pulse heights. Clearly, there are many particletrajectories that sample a large range of 1×1 values (and, hence, beamintensities), but only relatively few that probe the central portion ofthe gaussian profile, where the intensity is substantially uniform. ThePHD exhibits a broad, smooth upswing in the number of particles withincreasing pulse height, accelerating to a relatively sharp peak,followed by a dramatic decline to the baseline, representing zero pulseevents. This sharp “cut-off” at the upper end of the distributiondefines the maximum pulse height, referred to hereafter as ^(M)ΔV_(LE).The counts collected at this maximum value represent particles thatpassed through, or very close to, the center of the beam—i.e.trajectories with x approximately equal to 0—where the fraction of totalincident light flux “blocked” by the particles is the largest valuepossible. The counts collected in smaller pulse height channelsrepresent particles that passed further from the beam axis; the greaterparameter |x|, the smaller the resulting pulse heights.

There is a relationship between the particle trajectory and theresulting pulse height. Trajectory “A” gives rise to extinction pulseshaving the maximum pulse height, ^(M)ΔV_(LE), immediately preceding theupper cut-off of the PHD. Trajectories “B,” “C,” “D” and “E” locatedprogressively further from the beam axis, give rise to pulses withcorrespondingly lower pulse heights and progressively lower numbers ofparticle counts. Eventually, the number of particle counts per channelapproaches zero, as the pulse height reaches the detection limit(approximately equal to 5 mV).

The reproducibility of the PHD depends only on the degree to which thenumber of counts contained in the various channels are large compared tostatistical fluctuations. Therefore, the “reliability” (i.e. thesmoothness and reproducibility) of the PHD should depend on the totalnumber of particles counted during a measurement. For a given particlesize there will obviously exist a minimum number of pulses that shouldbe counted and analyzed, below which the PHD should be expected toexhibit significant, irreproducible “structure” from one measurement tothe next, due to statistical noise. Again, the PHDs produced by the newsensor have meaning only to the extent that relatively large,statistically meaningful numbers of particles of the same size aredetected during the data collection period. Only if this is true can oneexpect to obtain optimal, reproducible PHD results, and correspondinglyaccurate, representative particle size distribution (PSD) resultsderived from the latter using the methods discussed below.

To confirm that the data measured is significant, one can overlay two ormore PHDs taken from measuring the same sample in multiple runs.

Exposing the sensor to larger particles will yield a PHD that is shiftedto larger pulse heights. Specifically, the maximum pulse height,^(M)ΔV_(LE), corresponding to particle trajectories passing through, orvery close to, the beam axis, increases.

As shown in FIG. 2, the main design difference that distinguishes thenew LS-type sensor from its LE counterpart is the addition of a lightcollection means—typically one or more lenses—in order to gatherscattered light rays originating from individual particles passingthrough the OSZ, created by the incident light beam.

The lens system is designed to collect scattered light over aparticular, optimal range of angles, typically encompassing relativelysmall angles of scattering. In the scheme shown in FIG. 2, a mask 50 hasbeen placed in front of the first collection lens. Mask 50 comprises anouter opaque ring 52 and an inner opaque area 54, which form atransparent ring 56. Mask 50 allows only light rays with scatteringangles, theta, located within an imaginary annular cone defined byangles .theta₁ and theta₂ (i.e. theta_(1≦)theta₂) to impinge on thefirst collection lens 62. Typically, this lens is centered on the axisof the incident beam, at an appropriate distance (i.e. its focal length)from the center of the flow channel, causing a portion of the divergingscattered light rays from the OSZ to be captured by the lens and becomeapproximately collimated. A second lens 64 can then be used to focus theresulting parallel scattered rays onto a suitable (small-area) detectorDLs. The resulting signal is “conditioned” by one or more electroniccircuits, typically including the functions of current-to-voltageconversion and amplification.

There is a crucial difference between the signal, V_(LS), created bythis optical scheme and the signal, V_(LE), produced by the LE-typesensor. Unlike the latter, the LS-type sensor, by design, prevents theincident light beam emerging from the back window of the flow cell fromreaching the detector, D_(LS). Instead, the incident beam is either“trapped” by means of a suitable small opaque beam “stop” (e.g., theinner opaque area 54) or deflected by a small minor away from the lensthat is used to collect the scattered light rays originating from theOSZ. Consequently, the relatively large “baseline” level, V.sub.0,necessarily present in the overall signal, V_(LE), produced by theLE-type sensor is now absent from the LS signal, V_(LS). Ideally, thenew “baseline” signal level is zero—i.e. there should be no scatteredlight generated from sources within the OSZ in the absence of aparticle. In practice, of course, there will be some amount ofbackground light caused by light scattered from the surfaces of thefront and/or back windows of the flow channel, due to imperfections on,or contaminants attached to, the latter surfaces. In addition, there maybe fluctuating background light due to scattering from small contaminantparticles suspended in the diluent fluid. Also, for some samples theremay be fluctuations in background light produced by a “sea” ofultra-fine particles which comprise a major fraction of the overallparticle population, but which are too small to be detectedindividually.

When a particle of sufficient size passes through the OSZ, defined bythe incident gaussian light beam and front and back windows of flowchannel 35, a momentary pulse occurs in the output signal produced bythe detector, D_(LS), and associated signal-conditioning circuit. Ingeneral, one might naively expect that the larger the particle, thegreater the amount of light scattered by it, assuming the sametrajectory, and therefore the greater the height of the signal pulse.

In practice, the actual pulse height depends not only on the size of theparticle, but also its composition—specifically, its index of refraction(and that of the surrounding fluid) and absorbance, if any, at theincident wavelength. The pulse height also depends on the wavelength ofthe beam and the orientation of the particle as it passes through theOSZ, if it is not spherical and homogeneous. Finally, for particlescomparable in size to, or larger than, the wavelength, the scatteringintensity varies significantly with the scattering angle. Consequently,in this case the pulse height depends on the range of angles over whichthe scattered light is collected and measured.

The relationship between the scattered light “radiation pattern” (i.e.intensity vs angle) and all of these variables is described by classicalMie scattering theory, which takes into account the mutual interferenceof the scattered light waves within the particle. In general, the largerthe particle, the more complex (i.e. non-isotropic) the angulardependence of the scattered intensity resulting from intra-particleinterference. In order to optimize the response and performance of theLS-type sensor, one must confine the collection of scattered light to arange of angles, theta, for which the net integrated response, ΔV_(LE),increases monotonically with the diameter, d, of particles of a givencomposition (i.e. refractive index) over the largest possible, orexpected, size range. This requirement can usually be satisfied bychoosing a range of relatively small angles, theta₁<theta<theta₂, closeto the forward direction. In this way, one avoids “reversals” in theintegrated scattering intensity with increasing particle size due tovariations of the intensity with changes in angle, especiallysignificant at larger angles as a consequence of Mie intra-particleinterference.

There are two properties of the signal, V_(LS), produced by the newLS-type sensor that are qualitatively different from the properties ofthe signal, V_(LE), produced by the corresponding LE-type sensor. First,the signal pulse caused by passage of a particle through the OSZ and the“overall” signal, V_(LS), are essentially the same in the case of theLS-type sensor. The relatively high background signal level thataccompanies the pulse of interest in the LE-type sensor is absent: (Thesame situation clearly holds for a conventional LS-type sensor).

Therefore, in the case of relatively small particles that give rise topulses of low magnitude, the signal/noise ratio achieved in practiceusing the LS method should be significantly better than that realizedusing the LE method. This advantage becomes more important the smallerthe particle and the weaker the resulting pulse, as the latterapproaches the prevailing noise fluctuations. Another way ofappreciating the inherent advantage of the LS method over its LEcounterpart is to realize that the former is based on “detection atnull.” That is, quantitative detection of a pulse ideally is carried outin the presence of zero background signal. From a signal/noiseperspective, this is in sharp contrast to the situation that obtains forthe LE method, which requires high “common-mode rejection.” The“common-mode” signal, V₀, is always present in the raw signal, V_(LE),and must be subtracted, or otherwise suppressed, in order to extract the(often small) signal pulse of interest.

There is a second important and distinguishing property of the LSsignal, V_(LS). The signal/noise ratio associated with the measurementof ΔV_(LS) can in principle be improved by increasing the power of theincident light beam, so as to increase the light intensity incident on aparticle at all points within the OSZ. Therefore, in principle one canreduce the lower size detection limit for the new LS sensor byincreasing the power of the light source, as for a conventional LSsensor. Eventually, a lowest size limit will be reached, based on noisefluctuations associated with the suspending fluid and/or the lightsource and detection system. Of course, as discussed above, the lowerparticle size limit can also be improved for the new LS-type sensor byreducing the width, 2w, of the incident beam, assuming no change in thepower of the latter. This action will obviously increase the maximumintensity incident on the particles that pass through the beam axis(x=0), and therefore the height of the largest resulting pulse for aparticle of given size, as well. However, this method of improving thesensitivity eventually reaches a point of diminishing return, due tolimitations imposed by diffraction theory (establishing a minimum beamwidth) and excessive variation of the focused beam width over the depth,b, of the flow cell due to excessively-long depth of field.

By contrast, an increase in the power of the light source has relativelylittle effect on the lowest particle size that can be measured using theLE method. For example, a doubling of the power of the light source willresult in a doubling of the baseline signal level (FIG. 2), to 2V₀. Theheight of the pulse, ΔV_(LE), produced by a particle of the same sizeand trajectory will also be doubled, assuming no change in the beamwidth. However, the root-mean-square magnitude of the noise fluctuationsassociated with the relatively high baseline signal level will typicallyalso be approximately doubled, because these fluctuations are usuallyassociated with the light source and therefore scale with the outputpower. Hence, one expects little or no improvement in the signal/noiselevel for the LE-type sensor. Consequently, there should be little or noreduction in the lower size detection limit achievable by the LE methodas a consequence of increasing the power of the light source. Animprovement will be realized only if the signal/noise ratio associatedwith the light source improves with increased power.

When uniform size particles flow through the new LS-type sensor,depending on their trajectories they are individually exposed todifferent values of maximum incident intensity, given by Equation 7,with r=x, z=0. (For simplicity, it can be assumed that the particles aremuch smaller than the beam width, so that every point in a givenparticle is exposed to the same intensity at any given time.) Therefore,as with the new LE-type sensor, the height, ΔV_(LS), of the resultingpulse generated by a particle of given size depends on the distance,|x|, of closest approach (z=0) to the axis of the incident beam. Thesmaller the distance |x|, the larger the value of ΔV_(LS). Hence, likeits LE counterpart, the LS-type sensor generates a distribution ofwidely varying pulse heights, ΔV_(LS), when a suspension of uniformparticles passes through it at an appropriate flow rate. The shape ofthe resulting PHD bears a strong qualitative resemblance to the highlyasymmetric shape of the PHDs obtained using the new LE method,exemplified in FIGS. 4, 6 and 7. That is, the number of pulse counts(y-axis) is relatively small at the smallest measurable pulse heightjust above the noise fluctuations) and rises with increasing pulseheight, ΔV_(LS). The pulse count value culminates in a peak value at amaximum pulse height, referred to as ^(M)ΔV_(LS), corresponding toparticle trajectories for which |x|.apprxeq.0. Above ΔΔV_(LS) the numberof pulse counts ideally falls to zero, assuming that the particleconcentration is below the coincidence concentration (discussed earlier)for particles of that size, so that at most one particle effectivelyoccupies the OSZ at any given time. Of course, a PHD obtained using thenew LS method usually pertains to particles that are smaller—oftensignificantly so—than those used to generate a typical PHD using the newLE method.

As noted above, the shape of the PHD—number of pulse counts vsΔV_(LS)-generated for uniform particles using the new LS method isqualitatively similar to the shape of the PHD obtained for uniform(typically larger) particles using the new LE method. Both kinds of PHDsshare the distinguishing characteristic of a sharp “cut-off” followingtheir respective peak number of pulse counts, coinciding with theirmaximum pulse height values, ^(M)ΔV_(LS) and ^(M)ΔV_(LE). However, itshould be appreciated that there are quantitative differences in theshapes of the two kinds of d=1, notwithstanding their qualitativesimilarities, even for the same particle size—e.g. d=1 μm. The “frontend” design of the new LS-type sensor—i.e. the focused light beam andrelatively thin flow cell—is essentially the same as that utilized forthe new LE-type sensor. Therefore, what distinguishes one type of sensorfrom the other concerns the means and manner of light detection and thetype and magnitude of the response pulses generated by each method, evenin the case of particles of the same size. For the new LS method, theresponse is due only to light scattering, and its magnitude, ΔV_(LS), isproportional to the intensity of the light incident on the particle, allother relevant variables being the same.

By contrast, for the new LE method the magnitude of the response,ΔV_(LE), is a more complex function of the intensity incident on theparticle. First, the response is due to a combination of physicaleffects—refraction (and reflection) plus light scattering. However, thescattering phenomenon asserts itself in an “inverse” sense. That is, asmall fraction of the incident light flux is removed from the beambefore it reaches the detector. Second, over the typical size range forwhich the new LE method is applicable, there is a substantial variationin the incident intensity across the particle. Therefore, it should notbe surprising that the fractional change of pulse height due to a givenchange in |x|, dependent on both particle size and trajectory, isgenerally different for the two methods. Similarly, the fractionalchange in pulse height with particle diameter, dependent on bothparticle size and trajectory, is also generally different for the twomethods.

The task of converting the “raw” data—the PHD—obtained from a sample ofsuspended particles into the object ultimately desired—the particle sizedistribution, or PSD, is described in detail below.

It is useful to compare this task conceptually with the operationrequired in the case of a conventional LE- or LS-type sensor. There, theheight of the pulse due to passage of a particle through the OSZ isnearly independent of its trajectory, because the intensity of theincident beam is designed to be approximately constant across the flowchannel (i.e. along the x-axis) for a given z-axis value (e.g. z=0).Consequently, particles of a given size ideally give rise to pulses ofsubstantially the same height, and the resulting PHD is therefore, ineffect, equivalent to the final desired PSD. There is a one-to-onecorrespondence between a given, measured pulse height, ΔV_(LE) (orΔV_(LS)), and the particle diameter, d. If particles of a larger orsmaller size pass through the sensor, the resulting pulse heights arelarger or smaller, respectively. A “calibration curve,” consisting ofpulse height vs particle diameter, is all that is needed to obtain, bysimple interpolation, the PSD from the PHD. Obtaining the raw PHD datausing the conventional SPOS method is equivalent to determining thefinal, desired PSD.

By contrast, as discussed earlier, the response of the LE- (or LS-) typesensor is much more “convoluted.” Even in the simplest case of particlesof a single size, the resulting PHD consists of a broad spectrum ofpulse heights, from the smallest values just above the prevailing noisefluctuations, to the maximum value, ^(M)ΔV_(LE) (or ^(M)ΔV_(LS)),associated with that size. Therefore, in the typical case of particlesof widely varying size, the resulting PHD consists of an even widerassortment of pulse heights. No longer is there a simple correspondencebetween pulse height and particle size. It is therefore no longer asimple, straightforward procedure to transform the set of particlecounts vs pulse-height values contained in the PHD into the desired sizedistribution—particle counts vs particle diameter.

It typically involves three procedures to convert the PHD to the desiredPSD. First, the raw PHD must be inverted, or deconvoluted, using aspecialized mathematical algorithm. Its purpose is to convert the“wide-spectrum” PHD produced by the new LE- (or LS—) type sensor into a“sharp”, idealized PHD, equivalent, in effect, to what would have beenobtained using a conventional LE- (or LS-) type sensor. Such anidealized, deconvoluted PHD—hereinafter referred to as the dPHD—has theproperty that all pulses of a given height, ΔV_(LE) (or ΔV_(LS)), belongexclusively to particles of a given size (assuming, always, particles ofa given composition). The dPHD is equivalent to what would have beenobtained if all of the particles contributing to the original PHD hadpassed through the center (axis) of the incident beam.

A second straightforward procedure is then carried out. A preliminary,or “raw”, PSD is obtained from the dPHD by simple interpolation of thecalibration curve that applies to the specific new LE- (or LS-) typesensor utilized—e.g. the curve shown in FIG. 8A. This procedure permitsa one-to-one translation of each deconvoluted pulse height value in thedPHD into a unique particle diameter associated with this value, thusyielding the raw PSD. A third procedure is then needed to convert theraw PSD thus obtained into a final PSD that is quantitatively accurate.The number of particle counts in each diameter channel of the raw PSD isthe number of this size that actually contributed to the measured PHD.As discussed above, this is typically only a small fraction of the totalnumber of particles of the same size (i.e. within the size range definedby the diameter channel) residing in the volume of sample suspensionthat passed through the sensor during data collection. This fraction,phi_(d), of particles actually detected by the new LE- (or LS-) typesensor varies significantly with the particle diameter, d.

The third procedure involves multiplying the number of particlescontained in each diameter channel of the raw PSD by the value of 1/phi₁that applies for that channel. This operation yields the final, desiredPSD, describing the number of particles of each size estimated to residein the quantity of sample suspension that passed through the sensorduring data acquisition. Values of 1/phi_(d) for each value of diameter,d, can be obtained from the sensor efficiency curve, phi_(d) vs d, byinterpolation.

There are two independent algorithms presented herein for deconvolutinga measured PHD, to obtain the dPHD, hereinafter referred to as “matrixinversion” and “successive subtraction.” Implementation of eitherprocedure is based on the property that the response of the new LE- (orLS-) type sensor—like its conventional SPOS counterpart—is additive.Because the particles passing through the sensor give rise to signalpulses one at a time, the resulting PHD can be considered to be composedof a linear combination, or weighted sum, of individual PHDscorresponding to uniform particles of various sizes, referred to as“basis vectors.” (This term is well known in linear algebra.) Each ofthese basis vectors represents the response of the system to astatistically significant number of particles of a single, given size.

A preferred embodiment of the focused light scattering device describedherein is shown in FIG. 3. The device incorporates both the new LE- andLS-type SPOS sensors of the invention in a single sensor, having twoindependent output signals, V_(LE) and V_(LS). The resulting dual“LE+LS” design offers increased capability and flexibility, providingsingle-particle counting and sizing over a relatively large range ofparticle sizes. The LS-type sensor subsystem can be used to extend thesize range below the lower detection limit provided by the new LE-typesensor subsystem. The extent to which the lower particle size limit canbe extended depends on a variety of parameters. These include: thewidth, 2w, of the narrow (typically focused) beam within the measurementflow cell; the power of the light source; the range of angles over whichscattered light is collected for implementation of the new LS-typesensing function; and the physical properties, including the refractiveindex, of both the particles and the suspending fluid.

The dual LE+LS sensor include a light source 160, preferably consistingof a laser diode module, typically having an output wavelength in therange of 600 to 1100 nanometers (nm). The beam 162 produced by the lightsource means preferably is collimated (parallel) and “circularized”—i.e.the intensity is a function only of the distance, r, from the centralaxis. Furthermore, the beam preferably has a gaussian intensity profile,as described by Equation 7, along any axis normal to the axis ofpropagation of the beam. The new LE+LS sensor also includes a focusingmeans 164, typically a single- or multi-element lens, capable offocusing the starting collimated light beam 162 to the desired beamwidth, 2w, at the center of the measurement flow channel 166 in the OSZ168, consistent with the desired particle size range. It is assumed thatthe focusing means has an appropriate focal length, thus yieldingacceptable values for both the width and depth of field of the focusedbeam. The latter is preferably significantly longer than the thickness,b, of the flow channel, in order to optimize the resolution of theresulting PSD.

The measurement flow cell 166 is fabricated from a suitable transparentmaterial, such as glass, quartz or sapphire, or alternativesemi-transparent material, such as PTFE (e.g. Teflon.™., manufactured byDuPont) or other suitable plastic that is sufficiently transparent atthe operating wavelength and compatible with the fluid-particle mixture.A suitable fluidics system, including a flow pump means and optionalmeans for automatic dilution of the starting sample suspension (ifneeded), are typically required to facilitate the steady flow of theparticle-fluid suspension through flow cell 166. The flow rate, F, isusually chosen to be the same as, or close to, the value used togenerate the calibration curve for the LE- or LS-type sensor.

The thickness, b, of the flow channel should be small enough to achievea high coincidence concentration limit and as uniform a beam width aspossible (ideally with b<<depth of field), resulting in improvedresolution for the final PSD. However, it must be large enough toprevent frequent clogging by over-size particles (e.g. agglomeratedprimaries and contaminants in the fluid/diluent). The width, a, of theflow channel is also chosen to strike a compromise between two competingeffects. A relatively large value reduces the impedance to the flowingfluid-particle mixture and lowers the velocity (and increases the pulsewidth) for a given flow rate, F. However, the larger parameter a, thesmaller the sensor efficiency, phi_(d), for any given particle diameter,d. This results in a smaller fraction of particles in the sampleactually contributing to the measured PHD and final PSD, which, if toosmall, may be undesirable.

The new LE+LS sensor contains two separate light collection anddetection subsystems, used independently to extract the desired LE- andLS-type signals. The LE-type signal can be captured using a small lightreflecting means M (e.g. mirror), positioned so as to intercept thenarrow beam 167 of incident light after it passes through the flow celland fluid-particle mixture. The resulting transmitted beam 169, thusdeflected away from the optical axis of the combined sensor, is causedto impinge on a nearby light detection means D_(LE). The lattertypically consists of a small-area, solid-state (silicon) detector,operating in a linear region and having a spectral response that ismatched to the wavelength of light source 160, thus providing an outputsignal with an acceptable signal/noise (S/N) ratio. The output of thedetector means is typically a current (the “photocurrent”), which can beconditioned by a current-to-voltage converter (“transimpedance”amplifier) 170, yielding an output signal in the generally desired formof a time-varying voltage, V_(LE(t)).

Alternatively, a small detector element can be placed directly in thepath of the light beam 167 after it emerges from the flow cell, thuseliminating the need for the intermediate light reflecting meansdiscussed above. Regardless of whether a mirror or detector element isused to “capture” the transmitted light beam, there are tworequirements. First, the means used must function as an effective beam“stop.” That is, it must be able to prevent any significant fraction ofthe arriving light flux from being reflected back toward the flow cell,thus becoming a source of “stray” light. Through unintended internalreflections from the various optical surfaces, a portion of the straylight can find its way to the scattering detection means D_(LS), thuscorrupting the resulting LS signal, by contributing a portion of theincident intensity to the latter. Second, the means used to capture theLE signal must be small enough not to intercept, and therefore block,scattered light rays at any angles that are intended to be captured andredirected to the light detection means D_(LS), as discussed below.

Separately, scattered light originating from particles passing throughOSZ 168 is collected over a range of scattering angles, theta, withtheta₁<theta<theta₂, where angles theta₁ and theta₂ are defined by asuitable aperture means, such as an annular mask 172 fabricated from aphotographic negative with an outer opaque portion 174, a transparentintermediate portion 176, and an inner opaque portion 178. The scatteredrays selected by mask 172 are allowed to impinge on a collecting lens180 of appropriate focal length and location, which converts thediverging scattered rays into an approximately parallel beam 182. Asecond lens 184 is then typically used to refocus the rays onto arelatively small light detection means D_(LS). As in the case of the LEsubsystem, the output signal of D_(LS) is typically a current, which canbe optionally conditioned, typically by means of a transimpedanceamplifier 186, so that the final output is in the form of a time-varyingvoltage, V_(LS(t)).

The signals V_(LE(t)) and V_(LS(t)) are organized into respective pulseheight distributions PHD by pulse height analyzers 188 and 189. The PHDsare then respectively deconvoluted in computer deconvolution means 190and 191, which ultimately compute a pair of respective particle sizedistributions PSD 192 and 193.

This embodiment can be implemented as an LE-type or LS-type sensor only,simply by removing (or not installing in the first place) the opticalelements, detection means and signal conditioning circuitry associatedwith the unwanted subsystem. In this case, it may be useful to adjustthe width, 2w, of the focused beam within the measurement flow channel,in order to optimize the resulting performance of the LE- or LS-typesensor. This parameter will impact the usable particle size range,coincidence concentration limit and minimum detectable particle sizedifferently for the two sensing modes, as discussed earlier.

II. Particles that can be Detected

Using the techniques described herein, various biological particles canbe detected. Cells are one type of biological particle that can bedetected. The method can be used to determine the presence or absence ofa specific type of cell in a given solution. For example, a sample ofblood, urine, spinal fluid, and the like can be evaluated for thepresence or absence of bacteria, fungi, viruses, and the like. Theparticle size, and, optionally, particle shape, can also provideinformation about the specific type of bacteria, fungi or virus.

III. Microparticles and Nanoparticles Suitable for Use in Focused LightScattering

In some embodiments, where the complex between an active agent and abiological particle does not result in a change in particle size (i.e.,no particle agglomeration or cell rupture), it may be necessary toconjugate the active agent with a microparticle (such as a nanoparticle,polystyrene bead, gold particle, and the like). Thus, when the agentforms a complex with the biological particle, the complex increases thesize of the biological particle by the size of the microparticle, andthis increased particle size is measurable using the techniquesdescribed herein.

In one embodiment, the particles have a particle size in the range ofbetween about 0.1 and 10 μm, and ideally have a relatively consistentamount of active agent bound to them. That is, if all that is importantis to determine that the biological particles bound to an active agentof interest, then one can simply incubate the biological particle withthe conjugate, and look for the decrease in peak corresponding to thebiological particle. This will confirm that a complex of the biologicalparticle and the active agent was formed.

If there is an interest in quantifying how much of the biologicalparticle was present, then it may be important to use particles with anearly uniform particle size, defined as having 90% or more of theparticles within 5% of the mean particle size, more preferably around99% uniformity or better. In addition to a uniform particle size, insome embodiments, it may be desirable to have uniform substitution onthe particles themselves. That is, rather than having particles of arelatively uniform particle size form complexes of different particlesizes with the biological particle of interest, it may be desirable toform complexes with a relatively uniform particle size, to ease theirquantification.

One way to produce particles with a relatively constant particle size,and with a relatively consistent amount of active agent conjugated tothe particles, is to use dendrimers. The dendrimers can include a knownquantity of the active agent, by virtue of the active functional groupsat the terminus on the dendrimers.

Another way is to produce polymer particles with: a) a relatively narrowsize distribution, and b) a relatively consistent amount of protectedfunctional groups, so that after the polymers are produced, theprotecting groups can be removed, and the functional groups used toconjugate the polymer particles to an active agent.

The active agent can be conjugated with the particle in such a way thatthe portion of the active agent that is known to be active (i.e., bindsa receptor) is not significantly sterically hindered by its conjugationwith the particle. In some embodiments, this will involve preparing ananalogue of the active agent which includes a further functional groupwhich can be attached to the particle.

In one embodiment, metallic particles, such as gold particles, are used.Because these particles scatter a significant amount of light, they canbe conjugated with a specific active agent, and used to identify evensmall molecules that bind to the agent. That is, the amount of lightthat the particle scatters is sufficiently large that the binding of theagent to the molecule of interest can be measured, even though themolecule is not within the size range of biological particles that canbe measured. Means for conjugating active agents to metallic particlesare known to those of skill in the art.

Metallic particles, such as gold particles, can also be used. These canbe conjugated with active agents using known methodology to formparticles capable of forming a complex with a biological particle,including particles too small to detect using focused light scatteringtechniques. Because the particles are highly dense, they produce enoughlight scattering to be detected, despite their small size. Binding ofeven a small molecule to the particles can be detected because of theintense scattering from the metallic bead so that enough light isscattered for the complex formation to be measured.

IV. Methods for Detecting the Presence or Absence of Specific Particlesin a Solution

A sample medium can be evaluated for the presence or absence of specificparticles. For example, a sample of blood, urine, spinal fluid, amnioticfluid, pleural fluid, peritoneal fluid and the like, can be evaluatedfor the presence or absence of specific microbes (cells (lymphocytes,B-cells, T-cells, neutrophils, monocytes, and the like), bacteria,fungi, viruses, and the like), and/or for the presence of relativelyhigh concentrations of white blood cells or other biological particlesindicative of a disease state. The methods also permit one to determinepresence or absence of shed particles.

The particle (intact cell, microparticle, bacteria, virus, fungus, andthe like) can be further identified and characterized by addition ofprobe particles that are coated with a specific agent that recognizesand binds to the specific surface epitope on the unknown particlesurface. If the recognition and binding of the probe particle occurs, anew particle size will be created and appear, thus identifying theunknown particle. For example if the unknown particle was a stem celland the probe particle was labeled with an anti-CD34 antibody, bindingof the probe particle with the stem cell would occur and a new sizedparticle would appear that would identify the presence of CD34 positivestem cells.

Once the particles are identified by size, one can confirm the identityof the particles, for example, by using a reference library correlatingthe particle size to a given biological species. Thus, in oneembodiment, the method involves comparing information obtained on abiological particle using focused light scattering techniques, with alibrary of data on biological particles obtained using similar focusedlight scattering techniques. The library can include information on twoor more biological particles, preferably, ten or more particles, morepreferably, one hundred or more particles, and, most preferably, morethan a thousand particles.

After a preliminary identification has been made on the type ofbiological particle, other biological techniques can optionally be usedto confirm the identity of the particle. For example, an EQELS spectraof the particle can be taken, and compared to a library of EQELS spectraof known particles, to confirm the identity of the particle.

Antibodies or other molecules specific for the specific biologicalparticle can be added to the solution, and if the particles bind to theantibodies, the method will detect the absence of the particles.Ideally, the molecules will be conjugated with a microparticle ornanoparticle, such as a latex particle. As the conjugate interacts witha biological particle, peaks representing the particle and the conjugatewill decrease, and peaks corresponding to the complex of the particleand the conjugate will increase.

In one embodiment, the biological particle is a microbe. The techniquecan be used to identify the type of microbe (i.e., bacteria, fungi, orvirus), and, ideally, the specific class of microbe (i.e., Pneumonia,Clostridia, and the like). In this embodiment, once a preliminaryidentification of the microbe is made, a confirmation assay can beconducted by first taking an EQELS spectra of the microbe in solution,subjecting the microbe to an antibody specific for the microbe, andtaking a second EQELS spectra. If the EQELS spectra are different, thisprovides confirmation that the microbe was properly identified and wasbound by the antibody. Further, once a microbe has been identified, aputative antimicrobial compound can be put in solution/suspension alongwith the microbe, to determine whether it is able to kill the microbe.

In one embodiment, the methods can be used to identify a potentialtherapeutic agent capable of interacting with a known cell, such as acancer cell, bacteria, fungi, or virus. In this embodiment, one firstuses focused light scattering techniques to generate a spectrum showingthe particle size and distribution for the known cancer cell, bacteria,fungi, or virus in a sample medium. Then, a putative therapeutic agentconjugated to a microparticle or nanoparticle is added to the samplemedium and allowed to incubate with the known cell, microbe or virus. Asecond spectrum is generated using focused light scattering techniques.If peaks corresponding to a complex of the microparticle-conjugatedtherapeutic agent and the known cell or microbe are observed, then thetherapeutic agent has bound to the cell. This is indicative of thepotential utility of the putative therapeutic agent against the knowncell, microbe or virus.

In one aspect of this embodiment, spectra of a microbe in a samplemedium are compared with a reference database of spectra of knownmicrobes, thus providing a rapid means for identifying a particularmicrobe. The spectra can also provide an initial determination ofparticle size and/or particle density in the medium.

Bacterial Detection

In one example of identifying microbes, one can determine whether themicrobes are mono-dispersed or poly-dispersed by their number and size.Since E. coli tend to mono-disperse and Streptococcus tend topoly-disperse, this embodiment can be used to observe particle size in asample, where observation of clumping identifies presence bacteria knownto clump (i.e. Streptococcus).

Detection of Particle Shedding:

In another embodiment, the method is used to detect particle shedding.Representative biological particles which shed smaller particles includetumors, red blood cells, white blood cells, granulocytes, platelets,monocytes, neutrophils, lymphocytes, endothelial cells, cancer cells,stem cells, bacteria, viruses, and fungi. Particle shedding may resultfrom cell interactions, a change of cellular state such as activation ordeactivation, as a result of expression, cell death, etc. The methodsdescribed herein can be used to identify such particle shedding.

In one embodiment, a drug or ligand is added to a vessel with a cell.Where the drug or ligand reacts with the cell, the cell may shedmembrane particles or other particles. As described in detail herein,the method can be used to detect the size, number and/or type ofparticles shed by the reaction. Therefore, where the cell is known, thistechnique may be used to detect efficacy of unknown drug agent; andwhere the drug is known, the technique may be used to identify thepresence of a specific cell type.

The ejected particles can be observed using the methods describedherein. The ejected particles can similarly be characterized bycomparing the size and/or shape with a library of data collected usingfocused light scattering techniques on known ejected particles, and/orby binding some or all of the ejected particles to an antibody or othersuch molecule.

A schematic illustration of shed particles binding to anantibody/microparticle conjugate is shown in FIGS. 4-7. FIG. 4 shows thesituation at time zero, before complex formation, and FIGS. 5-7 show thegradual formation of a complex, and the corresponding decrease in thepeaks associated with the shed particles and the microparticle/antibodyconjugate.

Detecting Individual Molecules

In one embodiment, the methods permit one to detect the presence ofspecific molecules, where the molecules are of a size below thethreshold limit of detection for focused light scattering techniques. Inthis embodiment, highly reflective metallic particles, such as goldparticles, are covalently linked to a ligand that binds to the moleculesof interest. Because the metallic particles are dense and highlyefficient light scattering particles, the amount of light scatteringwhen the ligand binds to a molecule of interest can be measured usingthe focused light scattering technique, thus confirming the presence orabsence of a molecule of interest in the solution. In anotherembodiment, microparticles conjugated to an active agent known to bindin a specific manner to a particular secies of shed particles are used,rather than metallic particles. The complex of the shed particle and themicroparticle is then measured. Representative agents include antibodiesand small molecules known to bind to the particular shed particles.

Detection of Particle Aggregation

In another embodiment, the method is used to determine particleaggregation and types of aggregation. Such aggregation may include, butis not limited to aggregation of a particle with other particles, oraggregation of a particle with a drug.

Particularly with respect to liposomal therapy, agglomeration ofparticles (such as liposomes) can result in significant mortality ormorbidity when the agglomerated particles are administered. Accordingly,the method can be used to evaluate a sample of liposomes beforeadministration to ensure that the particles have not agglomerated beforea patient is treated.

IV. Methods for Detecting Binding of a Particle to a Known Molecule

In some embodiments, one knows the identity of a known molecule, forexample, a drug molecule that is known to interact with the receptor ona biological particle that may or may not be present in the samplemedium. By incubating the sample medium with a conjugate of the drugmolecule and a microparticle, one can look for complex formationindicative of the binding of the drug molecule with biological particlesin the sample medium. The complex formation can be observed over time,or simply after a suitable incubation period.

The methods can be performed by using, as a starting material, either adrug or a biological microparticle in a vessel, and then adding a knownmaterial (either a known cell or microbe, for example) to test forinteraction with drug; or a known drug to test for interaction withmicroparticle). Then, focused light scattering techniques can beperformed to look for change in particle size from size of startingmaterial, where an increase or decrease in particle size is indicativeof interaction and binding.

In order to preserve the ability of the known molecule to bind to theparticle of interest, in those embodiments where a molecule isconjugated to a microparticle, it is conjugated in a way that does notadversely impact its ability to bind to the particle of interest. Thismay involve developing a modified molecule, wherein the molecule ismodified to include a functional group capable of being conjugated tothe microparticle, such that the molecule still maintains its ability toform a complex with the particle of interest. Such modifications areroutine in the art.

By using a biological particle known to form a complex with the activeagent, one can evaluate such modified compounds for their ability tomaintain their binding affinity for the particle of interest byincubating the modified compound, or the conjugate of the compound withthe microparticle with the particle. Those compounds which maintain theability to bind the particle of interest can be identified using focusedlight scattering techniques, because the particle size of the complex islarger than the particle size of the non-complexed particle andnon-complexed conjugate.

Column-Based Approaches to Removing Biological Particles

Rather than forming a complex of the biological particle and a conjugateof an active agent and a microparticle, one can optionally prepare acolumn including microparticles conjugated to agents that bind to thebiological particle of interest, and pass the sample medium through acolumn including the microparticles. The sample, minus any complexedbiological particles, will elute from the column. By performing thefocused light scattering method on the eluted material, one can identifychanges in particle number/population density, as compared to thestarting material. A decrease in particle number/population density isindicative of interaction and binding in the column, and, therefore, anindication that the biological particle of interest was present in thesample.

Magnetic Bead-Based Approaches to Remove Biological Particles

Rather than forming a complex of the biological particle and a conjugateof an active agent and a microparticle, and using focused lightscattering methods to identify the presence of the complex between thebiological particle and the conjugate, one can optionally use a magneticmicroparticle conjugated to the active agent. Thus, one can first obtaina focused light scattering spectra using the methods described herein,then use magnetic particles to complex with the biological particle ofinterest. The complex can be removed from the sample media using amagnet. Then, one can obtain a second focused light scattering spectra,and identify whether the number of biological particles of interest hasbeen reduced.

V. Methods for Determining Binding of a Known Particle to an UnknownCompound

In other embodiments, it is desired to learn whether a putativetherapeutic agent can bind to known biological particles. In theseembodiments, putative therapeutic agents are conjugated to amicroparticle or metallic nanoparticle, such as a gold nanoparticle, andincubated with the known biological particles. Thus, one can determinewhether a compound forms a complex with the biological particles.

In some aspects of this embodiment, it is desirable to know the minimuminhibitory concentration, or binding affinity, of an active agent. Theagent can be complexed with the biological particle at differingconcentrations, and this information can be obtained. Some degree ofextrapolation may be required, since the agent is conjugated to amicroparticle, and therefore may behave differently than the nativedrug.

In other aspects of this embodiment, it is desired to know theselectivity of an active agent for one receptor over another. In thisaspect, the agent can be complexed with a plurality of biologicalparticles expressing differing receptors, and binding information can beobtained for each of the receptors. Thus, selectivity can be determined.

Determining Therapeutic Activity/Efficacy/Selectivity

In another embodiment, the method is used to identify therapeuticagents. While small molecules, proteins and peptides are not likely tobe large enough to see, even with this technique, they can either becoupled to a microparticle, such as a latex particle or magnetic bead,which can be incubated with the molecules, or placed on a column.

In one aspect of this embodiment, a biological particle with a targetfor the therapeutic agent (i.e., a receptor) is placed in suspension,and microparticles conjugated to one or more putative therapeutic agentsare added to the suspension.

If the therapeutic agent binds to the biological particle, the bindingcan be observed because the size of the complex of the biologicalparticle and the conjugate is greater than that of the conjugate or thebiological particle.

This technique can be used, for example, to determine the efficacy ofspecific antibacterial or other drug candidates for a particularinfection, or to identify agents useful for treating specific types ofcancer. In one aspect of this embodiment, the techniques are useful forpersonalized medicine, where a particular patient's bacterial infection,platelet or cancer cells, or erythrocytes, are analyzed for theirability to bind to and interact with specific therapeutic agents. Inanother aspect of this embodiment, one can generate a plurality ofspectra and compare the results, to determine minimum inhibitoryconcentrations and, therefore, useful dosage ranges for a given drug(where the drug is an inhibitor).

VI. Methods for Identifying Patients Likely to Benefit from Treatment

Certain patients respond to therapy due to an interaction of a cellularreceptor with a drug molecule. However, certain other patients havegenetic mutations which do not permit the patients cells to bind to thedrug molecule, thus rendering the drug ineffective. To determine whethera patient will respond to a given therapy, a solution of the patient'scells can be combined with a drug molecule of interest, where themolecule is bound to a probe particle. microparticle or nanoparticle. Ifthe drug molecule of interest binds to the patient's cells, then theconcentration of the conjugate, and/or the patient's cells will belower, and a new peak corresponding to the complex of the cells and theconjugate will be observed. The absence of a new peak corresponding tothe complex of the cells and the conjugate is indicative that thepatient will not respond to the particular drug therapy. Thus, themethod can confirm that the patient will or will not achieve a benefitusing the particular drug therapy. This enables a personalized medicineapproach using rapid and inexpensive methods.

In one aspect of this embodiment, the cells are cancer cells from anindividual patient, and sample media containing the cancer cells areincubated with a series of therapeutic agents bound to a microparticleor nanoparticle. Those therapeutic agents that form a complex with thecancer cells are potential candidates for personalized treatment of thepatient, since they bind to and interact with the cancer cells. Thistechnique can provide a relatively quick and inexpensive method foridentifying patients who have certain mutations, such as HER2 positivepatients, patients whose cancer cells have vitamin D receptors, patientswith estrogen-responsive cancer cells, and the like.

In another aspect of this embodiment, the cells are blood cells from apatient suffering from atherosclerosis, and who is being evaluated tosee if his blood cells will respond to treatment with clopridogrelbisulfate (Plavix®). The interaction with the blood cells andclopidogrel bisulfate is a surface interaction, but a small percentageof patients have a mutation in their blood cells that inhibits thesurface interaction with this compound. For most of those patients,there is an alternative therapeutic agent, but it is important toidentify those patients before the symptoms worsen, possibly leading toa heart attack. In this aspect, blood cells of a patient are incubatedwith microparticles conjugated to clopidogrel bisulfate, and a spectrumis obtained using focused light scattering techniques. For exampleinteraction of the probe particle can be between the ADP receptor andPlavix target, P2Y12 or to the activation of the of VASP pathway. Thepresence of a complex between the clopidogrel bisulfate and the bloodcells can be observed. Further, if the patient is responsive to Plavix,no activation will occur when ADP or other specific agonists are addedto the patient's platelets. Thus, no activation will occur and specificactivation epitopes, like CD62, glycoprotein alpha2, beta3, etc., willbe detected by specific probe particles. Because the size of blood cellsand the microparticle/clopidogrel bisulfate conjugate are known, onlyone spectrum needs to be obtained, and the only peak of interest is thepeak corresponding to the complex of the conjugate with the blood cells.

VII. Methods for Performing High Throughput Bioassays

Any and all of these assays can be optimized for high throughputscreening using suitable robotics. Liquid handlers can transfer samplesto a multi-tube or multi-well plate, and a “memory map” can be used tocorrelate the samples to their location on the plate. Information oneach sample can then be stored, and used to provide information aboutdrug candidates, patient diagnoses, and proposed patient treatmentoptions.

Robotics systems are known in the art, and can be used to move samplestaken from individual patients to known positions in a multi-tube ormulti-well plate. Once information on the sample is obtained using thefocused light scattering techniques described herein, the informationcan be correlated to the individual patient via the stored informationcorrelating the location of the tube and the patient identification.Liquid handlers can take portions of the sample and evaluate a plurality(i.e., at least two) of different screening assays, for example, byincubating portions of the sample with different microparticles, boundto different active agents.

Automated processes using known robotics to pull and place samples (likehigh throughput screening) with use of a “memory map”. A user can thenpick desired screens to be run and the robotic apparatus will implementdesired processes.

In another aspect of the embodiments described herein, the methods canbe automated using robotics to pull and place samples (analogous toconventional high throughput screening methods), optionally inconjunction with a “memory map”. A user can then pick desired screens tobe performed, and the robotic apparatus can implement the desiredprocesses. In this embodiment, a laboratory can be set up toautomatically screen numerous samples.

In a preferred embodiment, the personalized medicine processes describedherein are automated, to provide relatively inexpensive, and relativelyfast, high throughput screening methods to identify preferred therapiesfor patients suffering from disease.

VIII. Reference Libraries

A reference database of information gained by performing focused lightscattering on known compounds can be used. One can compare the sample tothe reference database in order to identify or characterize theparticles in the tested sample. A reference database includes at leasttwo, preferably more than ten, more preferably greater than a hundred,and most preferably, greater than a thousand bits of information onparticle size that can be used to correlate the particle size measuredusing the techniques described herein with particle sizes for knownbiological particles that are stored in the reference database.

The present invention will be better described with reference to thefollowing non-limiting examples.

GENERAL EXAMPLES

Process steps: 1) obtain sample of pleural fluid with suspected bacteriapresence; 2) utilize focused light scattering to identify the presenceof a bacteria by its particle size and/or shape, compare bacterialspectra with known bacterial spectra, which allows one to identifybacteria present in fluid; 3) add an antibody agent specific for aunique marker on the now known bacteria to confirm bacterial identity;4) observe characteristic swim rate (for example, using EQELS) offlagella on certain bacteria to confirm bacterial identity. One candetermine the binding constant of a putative antimicrobial agent, whichcan help determine the minimum inhibitory concentration (MIC) for apotential drug candidate. Not all of the above steps have to be usedtogether every time. The above process is equally applicable foridentifying viruses or fungi in a biological sample.

The following examples are intended to illustrate, but not limit theinvention.

Example 1 Detection of Microparticle's (MP) Present in a BiologicalSample

In this example, a specimen is subject to particle sizing and counting.After an appropriate dilution of the sample, the diluted specimen isintroduced into the device for analysis. As counting proceeds, countswill accumulate in the size region less that 1 micron. The appearance ofMP in this size region will indicate the presence of MP's.

Example 2 Microparticle Characterization

Once MP's are detected, as described in Example 1, it may be importantto determine the source of the MP (from platelets neutrophils, tumorcell, etc.). This Example provides two different options forcharacterizing the MP.

The first option is to use MP sizing and counts. In this case, thespecimen is incubated with a second particle with a specific ligandconjugated to its surface. The choice of the ligand will depend on thespecific MP be characterized. For example, if the MP of interest hascoagulation tissue factor (TF) on its surface, the conjugated particlecan be conjugated with an antibody against TF-particle or withcoagulation factor FVII. Either ligand will specifically bind to MP'swith TF on their surfaces.

When the conjugated particles are incubated with the anti-TF conjugatedparticles, a new size corresponding to the TF-MP+anti-TF-particles willappear when the MP and the probe particle are counted. In a like manner,other MP's can be characterized by developing probe particles with aconjugated ligand specific for the MP of interest.

The second option is to use an EQELS device to analyze the MP's. Thebasic procedure is the same, except that differences in the particleselectrophoretic mobility can be analyzed.

Specifically, a baseline electrophoretic mobility of the MP can beobtained. The MP will then be mixed with the probe particle that isconjugated with the specific ligand for the MP of interest, or just withthe ligand without conjugation to a probe particle. When the probeparticle binds to the MP of interest, a difference in theelectrophoretic mobility is observed. These data will provide a specificidentification of the MP. If the ligand alone was used to bind to theMP, the EQELS data, in addition to IP of the particle, will also providebinding constants for the ligand to the MP.

Example 3 Determination of Cellular Activation

In this Example, the cellular activation, such as platelet activation,is determined. A baseline resting platelet run on the sizing-countingdevice is determined. The platelet or cell is then activated usingappropriate agonists. Once activation occurs, new surface epitopesappear on the surface. In the case of the platelet DC62, CD41, variousintegrins, and the like, begin to appear.

A probe particle with a ligand for the specific epitope of interest isthen added to the activated platelets (or other cells). The ligand canbe an antibody, or small molecule, that specifically binds to theactivated epitope. When binding occurs, a particle is created (theactivated cell+the probe particle) which has a larger size than eitherthe activated cell or the probe particle. The appearance of these newparticles represents the appearance of the activated platelet+the boundprobe particle.

Example 4 Microbe Identification

In this Example, microbes are identified using the techniques describedherein. The microbe may be bacterial, viral, fungal, or protozoa. Asample containing a microbe is analyzed using the counting/sizing devicedescribed herein. The sample can be from a water supply, from a patient(human or animal), or other source. The size distribution will bedetermined, and compared to a database, to determine whether one or moreof the particles in the sample fall into any of the sizes typical forknown microbes. If so, a probe particle conjugated with a ligand thatspecifically binds to certain microbes can be added. The identity of themicrobe is confirmed when a new size distribution is obtained when thesample is incubated with the probe particle.

Additional verification can be obtained if the specimen is examined byEQELS, where a swim rate is determined for flagellated organisms usingthe velocimetry mode of the EQELS device. The EQELS device can alsodetermine the microbe's electrophoretic mobility. This information canbe compared with data in an EQELS database for further confirmation ofthe identity of the particle.

If indicated, EQELS will then be used to help determine the appropriateantimicrobial (antibiotic, antiviral, etc) agent. A know concentrationof antimicrobial agent will be added to the specimen. Binding of theagent to the microbe will be determined by a change in the microbe'selectrophoretic mobility. Further, if the drug kills the microbe, itssurface charge density changes resulting in a rather large change in thekilled microbe's electrophoretic mobility.

Example 5 Drug Efficacy: Effectiveness of Cell Inhibition

Specific Example of Aspirin or/and P2Y12 Inhibition of PlateletActivation

Platelet inhibition in arterial thrombophilic diseases is considered thestandard of care. Unfortunately, in some patients, conventional drugs donot inhibit the patient's platelets. Approximately 25% of ASA-treatedand 29% of Plavix-treated patients do not respond to treatment.Currently, there is no accepted assay to identify theresistant/refractory patients.

The assay described herein can use particle sizing, based on thefollowing concept, to identify resistant/refractory patients. The goalof treatment with anti-platelet drugs is to inhibit activation. When theplatelet is activated, new surface epitopes appear. So, in thisembodiment, the patient's platelets are first obtained as platelet richplasma (PRP). A baseline measurement of the particle size and/ordistribution is then made. Next, an aliquot of the patient PRP can bemixed with a platelet activator (agonist). If the drug works, noactivation occurs. If it does not work, the platelet will activate. Theassay can then probe the platelet surface for the appearance of newepitopes like CD62, CD41 and the like. The surface can be probed with aligand (antibody or otherwise) that is conjugated to a particle. Ifbinding occurs, the probe particle will bind with the activatedplatelet, and a particle with a different (larger) particle size (i.e.,the activated platelet+conjugated-probe particle) will appear. If thedrug works, no change in the particle size distribution will occur.

Example 6 Lipid Droplets as Drug Delivery Vehicles

Certain sized particles do not perfuse capillaries well. Since a typicalcapillary is approximately 2-3 microns in diameter, particles largerthat that size must have a surface to volume ratio that will permit thedistortion of the particle so that is can enter the capillary system;similar to a red blood cell. In this Example, particle sizing is used toidentify particles which fall into a range that will not be perfused,and result in potential malaise or death to the patient. Further, thesurface characteristics of some particles lead to instability, that maycause particle aggregation or fragmentation. Similar problems are wellrecognized in colloidal chemistry.

In this embodiment, drugs like Ambisome™, Daunosome™, Doxil, or otherliposomal drug delivery vehicles, can be screened for a safe particlesize distribution prior to infusion. The screen can identify particlesby particle size and distribution, so if relatively large particles,corresponding to agglomerated liposomal or other particles are observed,then the sample can be rejected before being infused. Alternatively, thesample can be subjected to conditions which de-agglomerate the particles(for example, ultrasound and the like), and the sample re-tested. Theseassays can also be used to optimize the solution, and particle surfaceoptimization for identifying the best lead compound(s).

Example 7 Small Molecule Distribution Assays. Specific Examples of vWFor Serum Plasma

vWF is a polydispersed molecule with a molecular weight distributionrange of 500,000 to 20 million or even higher. Thus, there is asubstantial difference in the molecular size distribution. Currenttechnology requires a minimum of several days to complete an analysis.

In this embodiment, gold beads are conjugated with an anti-vWF antibodyin a manner that would bind one bead to one vWF multimer. Since the massdensity of the gold bead results in more efficient light scattering, vWFmolecules bound to the gold beads will be visible to the focusedscattering sizing and counting device. Thus, the presence of, and insome embodiments, the amount of, vWF can be determined.

Although the invention has been described with reference to the aboveexamples, it will be understood that modifications and variations areencompassed within the spirit and scope of the invention. Accordingly,the invention is limited only by the following claims.

1-29. (canceled)
 30. A method of identifying particle aggregation in asample medium comprising: a) generating a first spectrum showingparticle size and distribution, using focused light scatteringtechniques, for a sample medium comprising a biological particle;wherein the presence of a peak corresponding to the particle size ofaggregated particles is indicative of the presence of an aggregate. 31.The method of claim 30, further comprising incubating the sample mediumwith an active agent which promotes or inhibits particle aggregation inthe absence of a specific mutation in the biological particle, whereinthe development of, or lack of development of, particle aggregationprovides information on the activity, or lack of activity, of the activeagent against this particular biological particle.
 32. The method ofclaim 31, wherein the biological microparticles comprise platelets. 33.The method of claim 32, wherein the active agent is clopidogrelbisulfate.
 34. A method of identifying particle aggregation in a samplemedium comprising platelets obtained from a patient to which Clopidogrelbisulfate has been administered, comprising: a) adding a P2Y12 agonistto the medium in an amount that would cause platelet aggregation if thepatient is non-responsive to Clopidogrel bisulfate, wherein the absenceof platelet aggregation is indicative of the patient being responsive toClopidogrel bisulfate, and the presence of platelet aggregation isindicative of the patient being non-responsive to Clopidogrel bisulfate,and b) generating a spectrum showing the particle size and distributionof the platelets using focused light scattering techniques; wherein thepresence of a peak corresponding to the particle size of aggregatedplatelets is indicative of the patient being non-responsive toClopidogrel bisulfate, and wherein the absence of a peak correspondingto the particle size of aggregated platelets is indicative of thepatient being responsive to Clopidogrel bisulfate.
 35. The method ofclaim 34, wherein the P2Y12 agonist is adenosine diphosphate.